Method and system for optimizing combustion of heating furnace based on rolling force feedback

Abstract

The invention discloses a method for optimizing combustion of a heating furnace based on rolling force feedback, which relates to the technical field of steel rolling and comprises the following steps: a control rule set is set, the control rule set comprises a plurality of control rules, and each control rule comprises a difference value between an actual rolling force and a target rolling force and a corresponding furnace temperature adjusting strategy; operating data of the rolling mill are collected, the collected operating data are preprocessed, and actual rolling force is obtained; the control rule is called based on the actual rolling force, and a control instruction is generated based on the control rule; and adjusting and controlling the furnace temperature of the heating furnace based on the control instruction. The temperature of the heating furnace is automatically adjusted through rolling force feedback of the rolling mill, maintenance is easy, and operation of field operators is facilitated.

Description

Technical Field

[0001] This invention relates to the field of steel rolling technology, and in particular to a method and system for optimizing combustion in a heating furnace based on rolling force feedback. Background Technology

[0002] Currently, automatic combustion technology is widely used in steel rolling furnaces to achieve precise control of the combustion process. However, many factors influence automatic combustion, such as fuel characteristics, furnace structure, burner design, furnace atmosphere, and control system. These factors interact with each other, jointly affecting the combustion efficiency and thermal efficiency of the furnace.

[0003] Although automatic combustion technology has achieved some success in the application of steel rolling furnaces, several challenges remain. First, traditional fuels are unstable and easily produce harmful substances such as CO and nitrogen oxides during combustion, posing risks to human health and causing serious environmental pollution. Second, unreasonable furnace structure and burner design lead to incomplete fuel combustion and low thermal efficiency. Furthermore, the control system lacks precision, making it difficult to accurately control the combustion process, thus affecting the furnace's combustion efficiency. However, with the continuous improvement of furnace technology, these challenges are gradually being resolved.

[0004] It is worth noting that the steel billets heated in the heating furnace serve the rolling mill. Providing the rolling mill with reasonable billets is the main indicator for evaluating the quality of the heating furnace's automatic combustion system. Fluctuations in rolling force are often the internal cause of product size fluctuations, but currently very few people have considered this aspect. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a method and system for optimizing combustion in a heating furnace based on rolling force feedback.

[0006] To solve the above technical problems, the technical solution of the present invention is as follows: A method for optimizing combustion in a heating furnace based on rolling force feedback includes: A control rule set is set, which includes several control rules, and each control rule includes the difference between the actual rolling force and the target rolling force and the corresponding furnace temperature adjustment strategy. Collect the operating data of the rolling mill and preprocess the collected operating data to obtain the actual rolling force; The control rules are retrieved based on the actual rolling force, and control commands are generated based on the control rules. The furnace temperature is adjusted and controlled based on the control commands.

[0007] As a preferred embodiment of the method for optimizing furnace combustion based on rolling force feedback described in this invention, the actual rolling force includes the actual roughing rolling force and the actual finishing rolling force, and the target rolling force includes the target roughing rolling force and the target finishing rolling force.

[0008] As a preferred embodiment of the method for optimizing furnace combustion based on rolling force feedback described in this invention, the control rule set includes: When the absolute value of the difference between the actual roughing rolling force and the target roughing rolling force is less than or equal to 60, maintain the current furnace temperature; When the actual roughing rolling force is less than the target roughing rolling force and the difference between the two is greater than 60, the furnace temperature is controlled to rise. When the actual roughing rolling force is greater than the target roughing rolling force and the difference between the two is greater than 60, the furnace temperature is controlled to decrease. When the absolute value of the difference between the actual finishing rolling force and the target finishing rolling force is less than or equal to 30, maintain the current furnace temperature; When the actual finishing rolling force is less than the target finishing rolling force and the difference between the two is greater than 30, the furnace temperature is controlled to rise. When the actual finishing rolling force is greater than the target finishing rolling force and the difference between the two is greater than 30, the furnace temperature is controlled to decrease.

[0009] As a preferred embodiment of the method for optimizing furnace combustion based on rolling force feedback described in this invention, the amount of adjustment of furnace temperature in a single operation is less than or equal to the target value.

[0010] As a preferred embodiment of the method for optimizing furnace combustion based on rolling force feedback described in this invention, the step of collecting the operating data of the rolling mill and preprocessing the collected operating data to obtain the actual rolling force includes: The actual rolling force is obtained by collecting operating data over several consecutive sampling periods and averaging the collected rolling force parameters.

[0011] As a preferred embodiment of the method for optimizing furnace combustion based on rolling force feedback described in this invention, the number of sampling cycles is eight.

[0012] The present invention also provides a system for optimizing furnace combustion based on rolling force feedback, comprising: The rule setting module is used to set a set of control rules. The set of control rules includes several control rules, and each control rule includes the difference between the actual rolling force and the target rolling force and the corresponding furnace temperature adjustment strategy. The data acquisition module is used to collect the operating data of the rolling mill and preprocess the collected operating data to obtain the actual rolling force. The rule retrieval module is used to retrieve the control rules based on the actual rolling force and generate control instructions based on the control rules; The furnace temperature regulation module is used to regulate and control the furnace temperature based on the control commands.

[0013] The beneficial effects of this invention are: (1) The present invention automatically adjusts the temperature of the heating furnace through the rolling force feedback of the rolling mill, which is easy to maintain and convenient for on-site operators.

[0014] (2) The present invention can effectively avoid decarburization, burn-off and fuel consumption caused by excessive heating temperature, and can also prevent excessive heating temperature, excessive rolling mill load, and increase in roll consumption and power consumption. At the same time, it can stabilize the rolling force within the control range, thereby further improving the dimensional accuracy and plate shape of the rolled products and improving product performance.

[0015] (3) The present invention achieves optimal economic temperature control by optimally matching heating temperature with rolling mill load, and reduces furnace fuel consumption by more than 3%. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of the method for optimizing furnace combustion based on rolling force feedback provided by the present invention. Figure 2 This is a schematic diagram of the expert controller in the system for optimizing combustion in a heating furnace based on rolling force feedback provided by the present invention. Detailed Implementation

[0018] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0019] Figure 1 This is a schematic flowchart illustrating a method for optimizing furnace combustion based on rolling force feedback, provided in an embodiment of this application. The method specifically includes the following steps: Step S101: Set a control rule set. The control rule set includes several control rules, and each control rule includes the difference between the actual rolling force and the target rolling force and the corresponding furnace temperature adjustment strategy.

[0020] Specifically, based on on-site research and summarizing the experience of skilled operators, combined with theoretical knowledge, a set of control rules is constructed using the production rule "If A, then B," where A is the premise or condition, and B is the conclusion. The relationship between A and B can take various forms, such as analytical expressions, fuzzy relations, empirical rules of causal relationships, etc.

[0021] In this embodiment, the above-mentioned control rule set includes the following control rules: R1: When the absolute value of the difference between the actual roughing rolling force and the target roughing rolling force is less than or equal to 60, maintain the current furnace temperature; R2: When the actual roughing rolling force is less than the target roughing rolling force and the difference between the two is greater than 60, control the furnace temperature to rise; R3: When the actual roughing rolling force is greater than the target roughing rolling force and the difference between the two is greater than 60, control the furnace temperature to decrease; R4: When the absolute value of the difference between the actual finishing rolling force and the target finishing rolling force is less than or equal to 30, maintain the current furnace temperature; R5: When the actual finishing rolling force is less than the target finishing rolling force and the difference between the two is greater than 30, control the furnace temperature to rise; R6: When the actual finishing rolling force is greater than the target finishing rolling force and the difference between the two is greater than 30, control the furnace temperature to decrease.

[0022] Step S102: Collect the operating data of the rolling mill and preprocess the collected operating data to obtain the actual rolling force.

[0023] Specifically, the system collects operating data from the rolling mill. In this embodiment, the data primarily originates from feedback information from its closed-loop control system and input information. Processing this information yields useful control data such as the control system's error and its rate of change. Furthermore, information processing includes necessary filtering measures. The main function of a computer control system is to monitor, control, and manage the production process. To achieve these functions, it is essential to acquire information from the production process in a timely manner and process this information appropriately, expressing it in a form easily understood by operators to control the production process. Additionally, to achieve closed-loop control, the system needs to perform calculations on these signals according to certain rules to generate the necessary control effects. Common data processing methods used in computer control systems include digital filtering and scaling transformation.

[0024] The scaling transformation is as follows: Using the rolling force output from the rolling mill as the control basis is obviously inconvenient for operators to understand; therefore, a scaling transformation is necessary to convert the rolling force into an actual operational basis. There are various scaling transformation methods, depending on the type of sensor used to measure the parameter. Several common scaling transformation methods include: linear transformation, formula transformation, and polynomial transformation. In this application, the measured parameter value and the transformation result have a linear relationship, so the linear transformation method is used.

[0025] Digital filtering is implemented as follows: In some production processes, abnormal rolling information may occur. An effective method is to use digital filters, which are implemented by a computer using a specific program, to reduce the proportion of abnormalities in the control signal. Commonly used digital filtering methods include: arithmetic mean method, coefficient filtering method, weighted average method, median method, etc. Information is mainly obtained through feedback information from closed-loop control and input information from the host computer. Through scaling transformation and digital filtering of the information, useful information for control, such as the error of the controlled variable, is obtained.

[0026] Furthermore, considering that the thermal process in the heating furnace is a slow-changing process, the control operation must have a time delay, and the control signals cannot be too frequent, otherwise furnace temperature oscillations will occur. Therefore, operating data is collected for eight consecutive sampling cycles, and the average value of the collected rolling force parameters is taken to obtain the actual rolling force. A control signal is issued once every eight sampling cycles.

[0027] Step S103: Retrieve control rules based on actual rolling force, and generate control commands based on control rules.

[0028] Specifically, the rolling mill data includes roughing and finishing rolling, and the heating furnace combustion system includes heating sections one, two, three, and a soaking zone. Based on the type and magnitude of the actual rolling force, the corresponding control rules are retrieved from the control rule set, and corresponding control commands are generated through the control rules, namely, maintaining the current furnace temperature, controlling the furnace temperature increase, and controlling the furnace temperature decrease.

[0029] Step S104: Adjust and control the furnace temperature based on control commands.

[0030] It should be noted that the adjustment amount of the furnace temperature in a single cycle is less than or equal to the target value. That is, each adjustment and control command is given with an appropriate and small adjustment amount. After multiple cycles of adjustment, the operating condition of the heating furnace gradually becomes stable.

[0031] In this embodiment, the adjustment amount of the furnace temperature in a single operation is 5~10℃.

[0032] In addition, this application also provides a system for optimizing furnace combustion based on rolling force feedback. The system includes: a rule setting module, a data acquisition module, a rule calling module, and a furnace temperature adjustment module.

[0033] Specifically, the rule setting module is used to set the control rule set. The control rule set includes several control rules, and each control rule includes the difference between the actual rolling force and the target rolling force and the corresponding furnace temperature adjustment strategy.

[0034] The data acquisition module collects the rolling mill's operating data and preprocesses it to obtain the actual rolling force. Data acquisition, analysis, and output belong to the expert controller system. In traditional controller design, the controller is based on control theory, and the object is described using quantitative physical models such as differential equations, difference equations, state equations, and transfer functions. These models can be obtained using mechanistic analysis or identification methods, and the designed controller is described using mathematical expressions. In the strip steel expert controller design, the controller is designed based on heuristic knowledge from field engineers and operators. The expert controller is the core of this system; it processes the rolling mill data, analyzes the furnace's operating status based on the processed data, and sends corresponding adjustment signals to the output module to control parameters such as the steel firing temperature, thereby ensuring the furnace operates under stable conditions. The main functions of the expert controller include data acquisition and processing, furnace temperature analysis and adjustment, and self-learning and revision of adjustment parameters. An expert controller typically consists of four parts: a knowledge base, a control rule set, an inference engine, and information acquisition and processing. Figure 2 As shown. The knowledge base consists of a fact set, an experience database, and a mathematical model database. To build a knowledge base, the problems of knowledge acquisition and knowledge representation must be solved. Knowledge acquisition involves how to obtain specialized knowledge and experience from domain experts. Knowledge representation refers to how to express and store knowledge in a form that computers can understand.

[0035] The rule invocation module is used to retrieve the control rules based on the actual rolling force and generate control instructions based on the control rules.

[0036] The furnace temperature regulation module is used to regulate and control the furnace temperature based on control commands.

[0037] Therefore, the technical solution of this application automatically adjusts the heating furnace temperature through rolling force feedback from the rolling mill. It is easy to maintain and convenient for on-site operators. By achieving optimal matching between heating temperature and rolling mill load, optimal economic temperature control is achieved, reducing heating furnace fuel consumption by more than 3%. Taking a rolling line with an annual output of 1 million tons as an example, with heating furnace fuel costs of 50 million yuan / year, it can generate a benefit of 1.5 million yuan / year; with oxidation loss reduced by 0.05% and the price difference between billet and iron oxide scale of 3,000 yuan / ton, it can generate a benefit of 1.5 million yuan / year, for a total benefit of 3 million yuan / year.

[0038] In addition to the above embodiments, the present invention may have other implementation methods; all technical solutions formed by equivalent substitution or equivalent transformation fall within the protection scope claimed by the present invention.

Claims

1. A method for optimizing combustion in a heating furnace based on rolling force feedback, characterized in that: include: A control rule set is set, which includes several control rules, and each control rule includes the difference between the actual rolling force and the target rolling force and the corresponding furnace temperature adjustment strategy. Collect the operating data of the rolling mill and preprocess the collected operating data to obtain the actual rolling force; The control rules are retrieved based on the actual rolling force, and control commands are generated based on the control rules. The furnace temperature is adjusted and controlled based on the control commands.

2. The method for optimizing furnace combustion based on rolling force feedback according to claim 1, characterized in that: The actual rolling force includes the actual roughing rolling force and the actual finishing rolling force, and the target rolling force includes the target roughing rolling force and the target finishing rolling force.

3. The method for optimizing furnace combustion based on rolling force feedback according to claim 2, characterized in that: The control rule set includes: When the absolute value of the difference between the actual roughing rolling force and the target roughing rolling force is less than or equal to 60, maintain the current furnace temperature; When the actual roughing rolling force is less than the target roughing rolling force and the difference between the two is greater than 60, the furnace temperature is controlled to rise. When the actual roughing rolling force is greater than the target roughing rolling force and the difference between the two is greater than 60, the furnace temperature is controlled to decrease. When the absolute value of the difference between the actual finishing rolling force and the target finishing rolling force is less than or equal to 30, maintain the current furnace temperature; When the actual finishing rolling force is less than the target finishing rolling force and the difference between the two is greater than 30, the furnace temperature is controlled to rise. When the actual finishing rolling force is greater than the target finishing rolling force and the difference between the two is greater than 30, the furnace temperature is controlled to decrease.

4. The method for optimizing furnace combustion based on rolling force feedback according to claim 3, characterized in that: The amount of temperature adjustment in a single operation is less than or equal to the target value.

5. The method for optimizing furnace combustion based on rolling force feedback according to claim 1, characterized in that: The process of collecting rolling mill operating data and preprocessing the collected data to obtain the actual rolling force includes: The actual rolling force is obtained by collecting operating data over several consecutive sampling periods and averaging the collected rolling force parameters.

6. The method for optimizing furnace combustion based on rolling force feedback according to claim 5, characterized in that: The number of sampling periods is eight.

7. A system for optimizing combustion in a heating furnace based on rolling force feedback, characterized in that: include: The rule setting module is used to set a set of control rules. The set of control rules includes several control rules, and each control rule includes the difference between the actual rolling force and the target rolling force and the corresponding furnace temperature adjustment strategy. The data acquisition module is used to collect the operating data of the rolling mill and preprocess the collected operating data to obtain the actual rolling force. The rule retrieval module is used to retrieve the control rules based on the actual rolling force and generate control instructions based on the control rules; The furnace temperature regulation module is used to regulate and control the furnace temperature based on the control commands.

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